3 papers
cs.CL2026
Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains
Yash Saxena, Ankur Padia, Mandar S Chaudhary +3
Retrieval-Augmented Generation (RAG) systems deployed in sensitive domains must provide interpretable evidence selection and robust safeguards against data poisoning, yet current a…
cs.IR2026
IMRNNs: An Efficient Method for Interpretable Dense Retrieval via Embedding Modulation
Yash Saxena, Ankur Padia, Kalpa Gunaratna +1
Interpretability in black-box dense retrievers remains a central challenge in Retrieval-Augmented Generation (RAG). Understanding how queries and documents semantically interact is…
cs.CL2025
Generation-Time vs. Post-hoc Citation: A Holistic Evaluation of LLM Attribution
Yash Saxena, Raviteja Bommireddy, Ankur Padia +1
Trustworthy Large Language Models (LLMs) must cite human-verifiable sources in high-stakes domains such as healthcare, law, academia, and finance, where even small errors can have…